Abstract
Two types of brain model are currently the center of a fundamental controversy in cognitive science. Traditional artificial intelligence models are based on the discrete, programmable symbol systems normally associated with Turing/von Neumann computation, and for which language and logic are the essential tools. This type of model is now being challenged by the rebirth of concurrent, distributed networks that are based on analog models of physical systems, and that also claim some similarity to neural architecture. In the former, discrete symbols are local, sequential, and rewritten under total program control. In the latter, symbols are only the end result of coherent network dynamics that need little explicit program control. The behavior of these networks is determined by the constraints within the network and the initial conditions. In this respect, network behavior is functionally similar to a complex measurement process, since measurement in physics discriminates and classifies implicate dynamical patterns by mapping them to explicit symbols. But what determines when a measurement is completed is an unresolved problem in physics, especially in quantum theory. It involves complementary modes of description, one based on the rate-dependent, continuous, time-symmetric dynamics of inexorable physical laws, and the other based on the rate-independent, discrete, irreversible constraints of programmable symbol systems. In physics, these modes are both distinguished and related only by measurement, but when a measurement occurs appears to be a matter of arbitrary choice. The brain uses many complementary modes of description, and must constantly choose among them, but the ultimate nature of this choice remains a problem.
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References
Bohr, N. (1934) Atomic Theory and the Description of Nature, Cambridge University Press, Cambridge, p. 67.
Bohr, N. (1949) Discussions with Einstein on epistemological problems in atomic physics, in Albert Einstein: Philosopher-Scientist, P. A. Schilpp, ed. Library of Living Philosophers, Evanston, Illinois.
Born, M. (1964) Symbol and reality, in The Natural Philosophy of Cause and Chance, M. Born, Dover, New York, Appendix 3.
Conrad, M. (1988) The brain-machine disanalogy, BioSystems 22 197–213.
Cowan, J. and Sharp, D. H. (1988) Neural nets and artificial intelligence, Dædalus 117, 85–121.
Delbrück, M. (1986) Mind from Matter, Blackwell Scientific Publications, Palo Alto, California.
d’Espagnat, B. (1983) In Search of Reality, Springer-Verlag, Berlin.
De Witt, B. and Graham, R. B. (1973) The Many Worlds Interpretation of Quantum Mechanics, Princeton University Press, Princeton, New Jersey.
Fodor, J. (1985) Précis of Modularity of Mind, The Behavioral and Brain Sciences 8, 1–42.
Fodor, J. and Pylyshyn, Z. (1988) Connectionism and cognitive architecture, in Connections and Symbols, S. Pinker and J. Mehler eds., MIT Press, Cambridge, Massachusetts, pp. 3–71.
Gibson, J. J. (1979) The Ecological Approach to Visual Perception, Houghton-Mifflin, Boston, Massachusetts.
Herbert, N. (1985) Quantum Reality, Anchor/Doubleday, Garden City, New York.
Kugler, P. and Turvey, M. (1987) Information, Natural Law, and the Self-assembly of Rhythmic Movement, Lawrence Erlbaum, Hillsdale, New Jersey.
Newell, A. (1980) Physical Symbol Systems, Cognitive Science 4, 135–183.
Pattee, H. H. (1967) Quantum mechanics, heredity, and the origin of life, J. Theoretical Biology 17, 410–420.
Pattee, H. H. (1979) The complementarity principle and the origin of macromolecular information, BioSystems 11, 217–226.
Pattee, H. H. (1982) Cell psychology: an evolutionary approach to the symbol-matter problem, Cognition and Brain Theory 5, 325–341
Pattee, H. H (1985) Universal principles of measurement and language function in evolving systems, in Complexity, Language and Life: Mathematical Approaches, J. Casti and A. Karlqvist, eds., Springer-Verlag, Berlin, pp. 268–281.
Penrose, R. (1989) The Emperor’s New Mind, Oxford University Press, Oxford.
Pylyshyn, Z. (1984) Cognition and Computation, MIT Press, Cambridge Massachusetts.
Smolensky, P. (1988) On the proper treatment of connectionism, Behavioral and Brain Sciences 11, 1–74.
Skarda, C. A. and Freeman, W. J. (1987) How brains make chaos in in order to make sense of the world, Behavioral and Brain Sciences 10, 161–195.
Toffoli, T. (1982) Physics and Computation, International J. of Theoretical Physics 21, 165–175.
von Neumann, J. (1955) Mathematical Foundations of Quantum Mechanics, Princeton University Press, Princeton, New Jersey.
Wheeler, J. A. and Zurek, W. H. Quantum Theory and Measurement, Princeton University Press, Princeton, New Jersey.
Wheeler, J. A. (1982) Bohr, Einstein, and the strange lesson of the quantum, in Mind in Nature, R. Q. Elvee, ed., Harper & Row, San Francisco, California, pp. 1–30.
Wigner, E. (1960) The unreasonable effectiveness of mathematics in the natural sciences, Communications in Pure and Applied Mathematics 13, 1–14.
Wigner, E. (1964) Events, laws, and invariance principles, Science 145, 995–999.
Wigner, E. (1982) The limitations of the validity of present-day physics, in Mind in Nature, R. Q. Elvee, ed., Harper & Row, San Francisco, California, pp.118–133.
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Pattee, H.H. (1992). The Measurement Problem in Physics, Computation, and Brain Theories. In: Carvallo, M.E. (eds) Nature, Cognition and System II. Theory and Decision Library, vol 10. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-2779-0_10
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DOI: https://doi.org/10.1007/978-94-011-2779-0_10
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